Building Scalable AI Agents with Modular Prompt Transpilation

I argue that monolithic system prompts fail at production scale, causing collaboration nightmares and hidden errors. By treating prompts as software artifacts, we can use modular skill files and a transpilation pipeline to enforce build-time validation, catch drift, and enable deterministic builds. This approach transforms prompt engineering into a robust build-system problem, allowing agents to safely propose their own instruction updates through standard code review processes.